code: def test_inference_of_fsdp_settings_for_swav_pretraining(
      self,
  ) -> None:
      overrides = [
          "config=pretrain/swav/swav_8node_resnet",
          "+config/pretrain/swav/models=regnet16Gf",
          "config.MODEL.AMP_PARAMS.USE_AMP=True",
          "config.OPTIMIZER.use_larc=True",
      ]
  
      cfg = self._create_config(overrides)
      self.assertEqual(cfg["MODEL"]["AMP_PARAMS"]["AMP_TYPE"], "apex")
      self.assertEqual(cfg.MODEL.HEAD.PARAMS[0][0], "swav_head")
      self.assertEqual(cfg.MODEL.TRUNK.NAME, "regnet")
      self.assertEqual(cfg.TRAINER.TASK_NAME, "self_supervision_task")
      self.assertEqual(cfg.OPTIMIZER.name, "sgd")
  
      cfg = self._create_config(
          overrides + ["config.MODEL.FSDP_CONFIG.AUTO_SETUP_FSDP=True"]
      )
      self.assertEqual(
          cfg["MODEL"]["AMP_PARAMS"]["AMP_TYPE"], "pytorch"
      )
      self.assertEqual(cfg.MODEL.HEAD.PARAMS[0][0], "swav_head_fsdp")
      self.assertEqual(cfg.MODEL.TRUNK.NAME, "regnet_fsdp")
      self.assertEqual(
          cfg.TRAINER.TASK_NAME, "self_supervision_fsdp_task"
      )
      self.assertEqual(cfg.OPTIMIZER.name, "sgd_fsdp")
  
file_path: vissl/tests/test_utils_hydra_config.py
imports: import unittest
  from typing import List
  from vissl.utils.hydra_config import compose_hydra_configuration, convert_to_attrdict, SweepHydraOverrides
label_desc: Use image node_id 3 for calling the TestUtilsHydraConfig obj's underlying member method code with example usage: obj.test_inference_of_fsdp_settings_for_swav_pretraining() without return types